1. 2019 Pavement Workshop May 21-23, 2019
Determining Pavement Design Criteria for Recycled Aggregate Base and Large Stone Subbase
TPF-5(341)
Bora Cetin
Assistant Professor
Iowa State University
+ 46 Associate Members

2. RESEARCH TEAM Iowa State University University of Wisconsin-Madison
Principal Investigator – Bora Cetin
Assistant Professor – Department of Civil, Construction & Environmental Engineering
Co-Principal Investigator – Ashley Buss
Co-Principal Investigator – Halil Ceylan
Professor – Department of Civil, Construction & Environmental Engineering
Co-Principal Investigator – Junxing Zheng
Research Personnel – Haluk Sinan Coban
PhD Student – Department of Civil, Construction & Environmental Engineering
University of Wisconsin-Madison
Co-Principal Investigator – William Likos
Professor – Department of Civil and Environmental Engineering
Co-Principal Investigator – Tuncer B. Edil
Professor Emeritus – Department of Civil and Environmental Engineering
Visiting Scholar – Askin Ozocak
Associate Professor – Sakarya University

3. OUTLINE Introduction Research motivation Objectives Research plan
Construction
Field testing
Laboratory testing
What have we learned?
Future expectations

4. INTRODUCTION Recycled concrete aggregate (RCA)
Old & failed concrete pavement surfaces
Other structures
Recycled asphalt pavement (RAP)
Old & failed asphalt pavement surfaces
Large stones
Single crushing operation
Energy consumption ↓ (Kazmee et al. 2015)
RCA
RAP
Large stones

5. RESEARCH MOTIVATION
Inconsistent design methods & construction specifications
Prediction of engineering properties from index properties
Variety & uncertainty of RCA and RAP
Limitations of the test apparatus for large stones

6. OBJECTIVES 1st Goal – Determine the field and laboratory performance
FWD, LWD, DCP, intelligent compaction (IC) data
Index & engineering properties
Unsaturated & saturated characteristics
2nd Goal – Develop a method to estimate the stiffness and permeability from
Percent crushing of particles after compaction
Sphericity, angularity, and surface texture
Gravel, sand, fines content, gravel-to-sand ratio, D10, D30, D50, D60
3rd Goal – Prepare a pavement design and construction specification
Performance
Life-cycle cost analysis

7. RESEARCH PLAN Task 1 – Literature review and recommendations
Task 2 – Tech transfer “state of practice”
Task 3 – Construction monitoring and reporting
Task 4 – Laboratory testing
Task 5 – Performance monitoring and reporting
Task 6 – Instrumentation
Task 7 – Pavement design criteria
Task 8 & 9 – Draft/final report
Green – Completed
Red – In Progress

8. CONSTRUCTION Test Facility
Minnesota Road Research Project (MnROAD) Low Volume Road (LVR)
Two-lane closed loop
Inside lane – traffic simulation
Outside lane – environmental & dynamic response monitoring

9. CONSTRUCTION Test Cells S. Granular Borrow = Select Granular Borrow
TX = Triaxial Geogrid
BX = Biaxial Geogrid
GT = Nonwoven Geotextile

10. CONSTRUCTION
Test Materials

11. FIELD TESTING Field Tests Lightweight deflectometer (LWD) test
Gas permeameter test (GPT)
Intelligent compaction (IC) test
Automated plate load testing (APLT)
Falling weight deflectometer (FWD) test

12. FIELD TESTING

13. Dynatest Model 8002 FWD device
FIELD TESTING
Falling Weight Deflectometer (FWD) Test
Geophones – 0 to 72 in (0 to 1830 mm) away from the center plate
Deflection basin
Influence depth = 1.5 to 2.2 in (0.45 to 0.68 m) (Mooney et al. 2010; Vennapusa et al. 2012)
Dynatest Model 8002 FWD device

14. FIELD TESTING Falling Weight Deflectometer (FWD) Test
Before & after paving
Composite analysis
Layered analysis
Asphalt
Base+subbase
Subgrade
Composite
Subgrade
Base+ subbase
Composite
Subgrade
Base+ subbase
Asphalt

15. FIELD TESTING
Falling Weight Deflectometer (FWD) Test
Before paving

16. FIELD TESTING
Falling Weight Deflectometer (FWD) Test
After paving

17. LABORATORY TESTING Task 4 - Laboratory Testing Iowa State University
Sieve analysis & hydrometer test
Atterberg limits
Proctor compaction
Specific gravity & absorption
Image analysis
Asphalt & cement content determination
Gyratory compaction & percent crushing
Contact angle measurement
University of Wisconsin-Madison
Permeability
Soil-water characteristic curve
Green – Completed
Red – In Progress

18. LABORATORY TESTING Sieve Analysis & Hydrometer Test
ASTM C136 & D6913 – Sieve analysis
ASTM D7928 – Hydrometer test
Material
Gravel (%)
Sand (%)
Fines (%)
Coarse RCA
61.7
34.9
3.4
Fine RCA
38.3
54.6
7.1
Limestone
52.3
32.6
15.1
RCA+RAP 41
50.4
8.6
Class 6 Aggregate
35.1
58.6
6.3
Class 5Q Aggregate
65.9
30.9
3.2
S. Granular Borrow
31.1
56.5
12.4
LSSB
99.6
0.3
0.1
Sand Subgrade
27.6
59.8
12.6
Clay Loam
3.1
37.2
59.7
Fines = silt and clay

19. LABORATORY TESTING Atterberg Limits Material LL PL PI Coarse RCA NA NP
Fine RCA
32.7
Limestone
17.9
RCA+RAP
27.4
Class 6 Aggregate
Class 5Q Aggregate
S. Granular Borrow
18.9
LSSB
Sand Subgrade
19.9
Clay Loam
36.3
23.9
12.4
LL = liquid limit; PL = plastic limit; PI = plasticity index; NA = not available; NP = non-plastic

20. LABORATORY TESTING Classification Material Gravel (%) Sand (%)
Fines (%) Cu Cc LL PL PI
USCS (ASTM D2487)
AASHTO M 145
Symbol
Definition
Coarse RCA
61.7
34.9
3.4
34.5
1.75 NA NP GW
Well-Graded Gravel with Sand
A-1-a
Fine RCA
38.3
54.6
7.1
33.9
1.12
32.7
SW-SM
Well-Graded Sand with Silt and Gravel
Limestone
52.3
32.6
15.1
211.3
1.91
17.9 GM
Silty Gravel with Sand
A-1-b
RCA+RAP 41
50.4
8.6
49.4
0.98
27.4
SP-SM
Poorly-Graded Sand with Silt and Gravel
Class 6 Aggregate
35.1
58.6
6.3
23.8
0.60
Class 5Q Aggregate
65.9
30.9
3.2
33.7
2.60
S. Granular Borrow
31.1
56.5
12.4
30.3
1.10
18.9 SM
Silty Sand with Gravel
LSSB
99.6
0.3
0.1
1.84
1.08 GP
Poorly-Graded Gravel
Sand Subgrade
27.6
59.8
12.6
33.1
1.24
19.9
Clay Loam
3.1
37.2
59.7
36.3
23.9 CL
Sandy Lean Clay
A-6
Fines = silt and clay; Cu = coefficient of uniformity; Cc = coefficient of curvature; LL = liquid limit; PL = plastic limit; PI = plasticity index; NA = not available; NP = non-plastic; USCS = unified soil classification system; AASHTO = American Association of State Highway and Transportation Officials

21. LABORATORY TESTING Specific Gravity & Absorption
ASTM C127 – for coarse aggregates
ASTM C128 – for fine aggregates
ASTM D854 – for soil solids
ASTM C127
ASTM C128
ASTM D854

22. Oven-Dry (OD) Specific Gravity Combined (Coarse + Fine)
LABORATORY TESTING
Specific Gravity & Absorption
Material
Oven-Dry (OD) Specific Gravity
Absorption (%)
Coarse
Fraction
Fine
Combined (Coarse + Fine)
Coarse RCA
2.40
2.00
2.25
4.05
11.68
6.97
Fine RCA
2.45
1.99
2.17
3.70
11.73
8.65
Limestone
2.65
2.68
2.66
1.91
1.51
1.72
RCA+RAP
2.47
2.15
2.28
3.09
5.22
4.34
Class 6 Aggregate
2.30
2.35
3.00
4.32
3.86
Class 5Q Aggregate
2.39
2.07
4.62
9.62
6.32
S. Granular Borrow
2.70
2.58
2.62
1.14
1.71
1.53
LSSB
2.60 NA
0.36
Sand Subgrade
2.56
1.08
2.13
1.84
Clay Loam
Coarse fraction = materials retained on No. 4 sieve; fine fraction = materials passing through No. 4 sieve; combined = weighted average of coarse and fine fractions

23. LABORATORY TESTING Proctor Compaction Material MDD OMC (%) (pcf)
(kN/m3)
Coarse RCA
122.9
19.31
11.3
Fine RCA
121.6
19.10
11.1
Limestone
142.2
22.34
6.2
RCA+RAP
125.6
19.73 10
Class 6 Aggregate
128.2
20.14
8.3
Class 5Q Aggregate
122.6
19.26 11
S. Granular Borrow
138.6
21.77
5.4
LSSB NA
Sand Subgrade
136.6
21.46
5.7
Clay Loam
123.9
19.46
MDD = maximum dry density; OMC = optimum moisture content; NA = not available

24. Oven-Dry (OD) Specific Gravity Combined Absorption (%)
LABORATORY TESTING
Summary of Other Index Properties
Material
MDD
OMC (%)
Combined
Oven-Dry (OD) Specific Gravity
Combined Absorption (%)
(pcf)
(kN/m3)
Coarse RCA
122.9
19.31
11.3
2.25
6.97
Fine RCA
121.6
19.10
11.1
2.17
8.65
Limestone
142.2
22.34
6.2
2.66
1.72
RCA+RAP
125.6
19.73 10
2.28
4.34
Class 6 Aggregate
128.2
20.14
8.3
2.35
3.86
Class 5Q Aggregate
122.6
19.26 11
6.32
S. Granular Borrow
138.6
21.77
5.4
2.62
1.53
LSSB NA
2.60
0.36
Sand Subgrade
136.6
21.46
5.7
1.84
Clay Loam
123.9
19.46
2.68
MDD = maximum dry density; OMC = optimum moisture content; NA = not available

25. LABORATORY TESTING Image Analysis 2D Particle Shape Analysis
Stereophotography
Shining 3D – EinScan-SP
Stereophotography
Shining 3D – EinScan-SP

26. LABORATORY TESTING Stereophotography Position 1 (Left) Position 2
Camera slider
Position 1
(Left)
Position 2
Position 3
(Right)
Camera
Test material
Position 1 (Left)
Position 2
Position 3 (Right)

27. LABORATORY TESTING Stereophotography Calibration
Background with text and shapes
for calibration

28. LABORATORY TESTING Stereophotography Parameters Stereophotography
Area sphericity
Diameter sphericity
Circle ratio sphericity
Perimeter sphericity
Width to length ratio sphericity
Circularity
Convexity
Roundness
Stereophotography
Several parameters can be determined by the stereophotography. Parameters are listed and a table is provided with their descriptions and formulas. In addition, their references are provided. This table is taken from one of Quan’s papers (not published yet I guess), who is Dr. Zheng’s PhD student.

29. LABORATORY TESTING Stereophotography
LSSB – 4766 particles (one barrel)
For the large stones, ISU team received 2 barrels from the MnDOT. Stereophotography was performed only for one of the barrels, which contains 4766 large stone particles retained on No. 4 sieve. Particles passing No. 4 sieve cannot be used for image analysis with the current image station setup. d1, d2, d3, and de parameters, which are related to particle sizes, are also obtained by the stereophotogtaphy. The equation of ‘de’ is also provided in this slide.
Particle size distribution of large stones were determined by both conventional sieve analysis and stereophotography. With the sieve analysis, percent passing values are determined by weight. On the other hand, with the stereophotography, percent passing values are determined by volume. As seen from the figure, image analysis and sieve analysis provided similar results. One comment is that now ISU team is working on improving the MATLAB codes to reduce noise and increase accuracy. Therefore, ISU team is expecting that the results will be much closer to each other after modifying the codes.
(Zheng and Hryciw 2017)

30. LABORATORY TESTING Stereophotography Stereophotography
Elongation ratio, flatness ratio, and elongation and flatness ratio can be determined from the data obtained by the stereophotography. Their scatter plots are provided in this slide. Distribution of the values among 4766 large stone particles are shown. From these figures, distribution of the ratios by percent finer by volume can be observed. Overall or weighted elongation ratio, flatness ratio, and elongation and flatness ratio can be determined. Further numerical analysis has not been performed yet because the ISU team is working on improving the MATLAB codes, which will change the values slightly. More accurate results will be shown later.
(Zheng and Hryciw 2017)

31. LABORATORY TESTING Stereophotography Stereophotography
In addition to the previous distributions, roundness (angularity) and sphericity values and their distributions can be determined. As said previously, no further data analysis has not been performed yet.

32. LABORATORY TESTING Stereophotography vs Shining 3D – EinScan-SP
Comparison
Randomly selected particles
For each sieve between 2.5-in and No. 4 sieves
Particles retained on 2.5-in sieve
Particles retained on 2-in sieve
Particles retained on 1.5-in sieve
Particles retained on 1-in sieve
To check the accuracy of the stereophotography, Shining 3D – EinScan-SP 3D scanner is also being used on selected particles. Since we need to scan the large stone particles one by one with the 3D scanner, 175 particles in total was selected for comparison. Sieve analysis was performed and the particles were separated based on their particles sizes. 25 particles from each sieve were collected. The pictures in this slide do not show all 25 particles retained on each sieve. The pictures are provided only to show the differences in particles sizes.
All 3D images were captured and their data are being analyzed right now. 3D image analysis data and their comparison with stereophotography will be provided later.
Particles retained on 3/4-in sieve
Particles retained on 3/8-in sieve
Particles retained on No. 4 sieve

33. LABORATORY TESTING Shining 3D – EinScan-SP White background for noise
elimination
Test material
This slide shows the Shining 3D – EinScan-SP setup. After several trials, we decided to place a white background to eliminate the noise that occurs frequently during scanning. After the placement of white background, the noise was reduced significantly. On the right-hand side, two examples are shown regarding the 3D images created.
EinScan-SP

34. LABORATORY TESTING Shining 3D – EinScan-SP Side view Top view
The data is saved in 3D Builder format. This slide only shows side and top views as an example of the created 3D image.

35. LABORATORY TESTING Asphalt Content Determination
Quantitative extraction – AASHTO T 164
Ignition method – AASHTO T 308
RCA+RAP  3.2% asphalt binder
Class 6 aggregate  3.3% asphalt binder
For asphalt content determination, both quantitative extraction and ignition methods were decided to be performed. Loss of fines is expected with the ignition method; therefore, higher-than-actual amount of asphalt binder can be determined. The reason is that fine asphalt particles have very low specific gravity, which means that they are lighter than other particles. During the ignition, burned asphalt turns into ash and collected by the fume hood. In addition to the ash, lightweight fine particles can also be collected by the fume.
Ignition method is very straightforward. To check the accuracy of the ignition method, quantitative extraction will also be used. So far, only two ignition tests could be completed for RCA+RAP and Class 6 aggregate materials. Other tests are in progress and their data will be provided shortly.
RCA+RAP
Class 6 Aggregate

36. Flexible wall permeameter
LABORATORY TESTING
Permeability Test
ASTM D5084
Specimens prepared in standard compaction mold
Flexible wall permeameter

37. LABORATORY TESTING
Permeability Test
DOC = degree of compaction

38. LABORATORY TESTING Permeability Test Degree of compaction
100, 95, and 90%

39. LABORATORY TESTING Soil-Water Characteristic Curve (SWCC) Test
ASTM D6836
Hanging column test  Pressure plate test
Cementation of RCA during the test period
Cementation of RCA
Pressure plates
Activity meter

40. LABORATORY TESTING Soil-Water Characteristic Curve (SWCC) Test
Van Genuchten (1980) model
Θ = θ − θ r θ s − θ r = αψ n m
Θ = Normalized volumetric water content
Θ = Soil volumetric water content
θ r = Residual volumetric water content
θ s = Saturated volumetric water content
Ψ = Matric suction
α, n, and m : Van Genuchten fitting parameters
Parameter
Value θr θs
0.2812 α
0.0317 n
1.2091 m
0.1730

41. LABORATORY TESTING
Soil-Water Characteristic Curve (SWCC) Test

42. LABORATORY TESTING Soil-Water Characteristic Curve (SWCC) Test
Degree of compaction ↓ initial volumetric water content ↑

43. WHAT HAVE WE LEARNED? Recycled Aggregate Base Layers
No considerable problem during construction
Stiffness of coarse & fine RCA > limestone & RCA+RAP
Cementation of unhydrated cement
Higher angularity and rougher surface texture
Stiffness of fine RCA > coarse RCA
Fines content ↑ unhydrated cement content ↑
Stiffness of RCA+RAP ≤ limestone
Literature → RCA & RAP > VA

44. WHAT HAVE WE LEARNED? Recycled Aggregate Base Layers
Stiffness of RCA+RAP < coarse & fine RCA
Literature → stiffness of RCA > RAP
Higher angularity and rougher surface texture
Hydrophobicity of RAP
Coarse & fine RCA → stress-hardening
Limestone & RCA+ RAP → stress-softening
Soft or wet subgrade condition

45. WHAT HAVE WE LEARNED?
Large Stone Subbase with or without Geosynthetics
Problematic construction of LSSB
Impracticality of two-lift construction for 18 in LSSB
Subgrade soil pumping due to large opening size of LSSB
Rutting
Varying stiffness in LSSB sections
May be due to compactability of LSSB
Stiffness of class 5Q < class 6
Speculations:
Instability of 9 in LSSB
Insufficient compaction of class 5Q
Suitability of 18 in LSSB
Effects of geosynthetics were not discernable

46. WHAT HAVE WE LEARNED? Test Materials Class 6 & class 5Q → not natural
Class 6 has some RAP
Class 5Q has some RCA
Clay loam → considerably lower Ksat than those of aggregates
Degree of compaction ↓ Ksat ↑
Cementation of RCA during tests
Good integrity between pressure plate and activity meter

47. FUTURE EXPECTATIONS
Compositions of materials – asphalt & cement content
Other physical properties – image analysis
Angularity and sphericity
Particle size distribution
Hydrophilicity & hydrophobicity – contact angle measurements
Degradation – gyratory compaction & percent crushing
Long-term performance evaluation

48. Thank You

49. REFERENCES
ACPA (2010). Why Recycle Concrete Pavements? TS043.1P. American Concrete Paving Association, Skokie, IL P /TS04 3.1P.pdf.
CalTrans (2015). Standard Specifications. California Department of Transportation, Sacramento, CA.
IDOT (2016). Standard Specifications for Road and Bridge Construction. Illinois Department of Transportation, Springfield, IL.
Kazmee, H., Mishra, D., & Tutumluer, E. (2015). Sustainable alternatives in low volume road base course applications evaluated through accelerated pavement testing. In IFCEE 2015 (pp ).
Kazmee, H., Tutumluer, E., & Beshears, S. (2016). Pavement working platforms constructed with large-size unconventional aggregates. Transportation Research Record: Journal of the Transportation Research Board, (2578), 1-11.
Li, C., Ashlock, J. C., White, D. J., Jahren, C. T., & Cetin, B. (2017). Gyratory abrasion with 2D image analysis test method for evaluation of mechanical degradation and changes in morphology and shear strength of compacted granular materials. Construction and Building Materials, 152,
MnDOT (2014a). Building Temperature Sensing Arrays (Thermocouple Trees), TCTree(April201 4).pdf.
MnDOT (2014b). Moisture Content – EW (EC, ET), pdfs/Base_Moisture_EC_EW_ET.pdf.
MoDOT (2018). Missouri Standard Specifications for Highway Construction. Missouri Highways and Transportations Comission.
Mooney, M., Rinehart, R., White, D., Vennapusa, P., Facas, N., & Musimbi, O. (2010). Intelligent soil compaction systems. NCHRP Report 676. National Cooperative Highway Research Program, Washington, D.C.
USGS (2018). Mineral Commodity Summaries. US Geological Survey.
Van Deusen, D., Burnham, T., Dai, S., Geib, J., Hanson, C., Izevbekhai, B., Johnson, E., Palek, L., Siekmeier, J., Vrtis, M., & Worel, B. (2018). Report on MnROAD construction activities. Report No. MN/RC Minnesota Department of Transportation, St. Paul, MN.
Vennapusa, P. K. R., White, D. J., Siekmeier, J., & Embacher, R. A. (2012). In situ mechanistic characterisations of granular pavement foundation layers. International Journal of Pavement Engineering, 13(1),
Vennapusa, P. K., & White, D. J. (2009). Comparison of light weight deflectometer measurements for pavement foundation materials. Geotechnical Testing Journal, 32(3), 1-13.
White, D. J., & Vennapusa, P. (2017) 2017 MnROAD unbound layer evaluation using intelligent compaction: Ingios validated intelligent compaction (VIC) results. Report No Ingios Geotechnics.
WisDOT (2018). Standard Specifications. Wisconsin Department of Transportation, WI.

50. Thank You!
QUESTIONS??

51. INTRODUCTION Flexible pavements Load distribution Aggregate base layer
90% of the paved roads
Load distribution
Aggregate base layer
Primary load carrying sublayer
Stiff and permeable
Subbase layer
Optional
Secondary load carrying sublayer
Separation
Working platform
Highly permeable

52. INTRODUCTION
1.33 billion tons of virgin aggregates (VAs) in 2017 (USGS 2018)
76% for roadway construction (USGS 2018)
Price of conventional VAs ↑ (ACPA 2010)
Alternative materials

53. LITERATURE REVIEW For RCA and RAP Angularity  RCA > RAP
Maximum dry  VA > RCA & RAP density
Optimum moisture  RCA > VA > RAP content
Hydrophobicity  RAP > RCA
Permeability  RAP > RCA
Stiffness  RCA & RAP > VA
Strength  RCA > VA > RAP
Durability  RCA > RAP > VA

54. LITERATURE REVIEW For LSSB
Limitations of laboratory equipment (Kazmee et al. 2016)
Inconsistent field data (Kazmee et al. 2016)
Fluctuation of the data
Mobilization of particles (Kazmee et al. 2016)
Large voids
Reorientation
Lack of design methods & construction specifications
Limited applications

55. CONSTRUCTION Large Stone Subbase Non-traditional subgrade preparation
Weak subgrade
DCP index between 2.5 – 3.5 in/blow (64 – 89 mm/blow)
Upper 1 ft (0.3 m)
Loosening & watering
(Van Deusen et al. 2018)
(White and Vennapusa 2017)

56. CONSTRUCTION Sensors Environmental monitoring
Thermocouples
Moisture probes
Dynamic response monitoring
Dynamic pressure cells
Geophones
Dynamic strain gauges
Thermocouple tree
(MnDOT 2014a)
Moisture probe
(MnDOT 2014b)
Dynamic pressure cell
Geophone
Dynamic strain gauge
(Van Deusen et al. 2018)
(Van Deusen et al. 2018)
(Van Deusen et al. 2018)

57. Environmental Sensors Dynamic Response Sensors Dynamic Pressure Cells
CONSTRUCTION
Sensors
TC = Thermocouple
EC = Moisture probe
PG = Dynamic pressure cell
GP = Geophone
LE = Longitudinal dynamic
strain gauge
TE = Transverse dynamic
Cell Number
Environmental Sensors
Dynamic Response Sensors
Thermocouples
Moisture Probes
Dynamic Pressure Cells
Geophones
Dynamic Strain Gauges
185 12 4 2 NA
186
188
189
127 3
728 16

58. CONSTRUCTION Recycled Aggregate Base Subgrade  Cells 185 & 186 – sand
Cells 188 & 189 – clay loam
Subbase  Select granular borrow
Base  Cell 185 – coarse RCA
Cell 186 – fine RCA
Cell 188 – limestone
Cell 189 – RCA+RAP blend
Surface  12.5 mm NMAS Superpave

59. CONSTRUCTION Large Stone Subbase
Non-traditional subgrade preparation – cont’d
Mellowing
Placement of LSSB
Impractical two-lift construction
(White and Vennapusa 2017)
(White and Vennapusa 2017)

60. CONSTRUCTION Large Stone Subbase with Geosynthetics Initial plan
Only two cells
No geosynthetics
Problems
Subgrade soil pumping
Rutting
(White and Vennapusa 2017)
(White and Vennapusa 2017)

61. CONSTRUCTION Large Stone Subbase with Geosynthetics
(Van Deusen et al. 2018)

62. CONSTRUCTION Large Stone Subbase with Geosynthetics
Excavation to subgrade layers
Reconstruction
Reconstruction

63. CONSTRUCTION Large Stone Subbase with Geosynthetics
Non-traditional subgrade preparation procedure
DCP index between 2.5 – 3.5 in/blow (64 – 89 mm/blow)
Geosynthetics
Triaxial geogrid (TX)
Biaxial geogrid (BX)
Nonwoven geotextile (GT)
(White and Vennapusa 2017)

64. FIELD TESTING Meteorological Data
Air temperature – 40°F (4°C) and 91°F (33°C) during construction
Relative humidity – 15% – 102%
Wind speed & direction
Precipitation

65. FIELD TESTING Nuclear Density Test
Direct transmission mode (ASTM D6938) for 60 seconds
4 in (102 mm), 6 in (152 mm), or 8 in (203 mm) deep test holes
Calibration with laboratory measurements

66. FIELD TESTING
Nuclear Density Test

67. FIELD TESTING Dynamic Cone Penetrometer (DCP) Test ASTM D6951
17.6 lb (8 kg) hammer
22.6 in (575 mm) drop height

68. FIELD TESTING Lightweight Deflectometer (LWD) Test ASTM E2835
Applied stress = 27.5 psi (190 kPa) (Vennapusa and White 2009)
Influence depth = 8 to 12 in (200 to 300 mm) (Mooney et al. 2010; Vennapusa et al. 2012)

69. FIELD TESTING Gas Permeameter Test (GPT)
GPT device containing a self-contained pressurized gas system with a self-sealing base plate.
Saturated hydraulic conductivity (KSat) is derived from gas flow and pressure measurements by using the Darcy’s Law.
(White et al. 2010)
S = saturation level

70. FIELD TESTING Intelligent Compaction (IC) Test Preliminary IC mapping
Automated plate load testing (APLT)
Cyclic stress-dependent resilient modulus (MR)
10 psi (69 kPa) and 30 psi (207 kPa) plate contact stresses
Influence depth = 2.5 to 5 ft (0.8 to 1.5 m) (Mooney et al. 2010; Vennapusa et al. 2012)
Vibratory smooth drum roller
IC mapping
APLT
(White and Vennapusa 2017)

71. FIELD TESTING Intelligent Compaction (IC) Test Before paving
Composite analysis
Layered analysis
Base+subbase
Subgrade
Composite
Subgrade
Base+ Subbase

72. FIELD TESTING
Intelligent Compaction (IC) Test

73. FIELD TESTING Automated Plate Load Testing (APLT)
(White and Vennapusa 2017)

74. FIELD TESTING
Automated Plate Load Testing (APLT)

75. FIELD TESTING Falling Weight Deflectometer (FWD) Test
Depth to water table

76. Fall cone penetrometer
LABORATORY TESTING
Atterberg Limits
BS – Liquid limit (fall cone penetrometer)
ASTM D4318 – Plastic limit (rolling device)
Materials with fines contents more than 5%
Material
Gravel (%)
Sand (%)
Fines (%)
Coarse RCA
61.7
34.9
3.4
Fine RCA
38.3
54.6
7.1
Limestone
52.3
32.6
15.1
RCA+RAP 41
50.4
8.6
Class 6 Aggregate
35.1
58.6
6.3
Class 5Q Aggregate
65.9
30.9
3.2
S. Granular Borrow
31.1
56.5
12.4
LSSB
99.6
0.3
0.1
Sand Subgrade
27.6
59.8
12.6
Clay Loam
3.1
37.2
59.7
Fall cone penetrometer
Rolling device
Fines = silt and clay

77. LABORATORY TESTING Atterberg Limits Material LL PL PI Coarse RCA NA NP
Fine RCA
32.7
Limestone
17.9
RCA+RAP
27.4
Class 6 Aggregate
Class 5Q Aggregate
S. Granular Borrow
18.9
LSSB
Sand Subgrade
19.9
Clay Loam
36.3
23.9
12.4
LL = liquid limit; PL = plastic limit;
PI = plasticity index; NA = not available; NP = non-plastic

78. LABORATORY TESTING Specific Gravity & Absorption
Three specific gravity terms (ASTM C127 & C128):
Oven-dry (OD) or bulk specific gravity
Saturated surface dry (SSD) specific gravity
Apparent specific gravity
Dry aggregate
Bulk volume 1.
SSD aggregate
Bulk volume 2.
Dry aggregate
Net volume 3.

79. LABORATORY TESTING Proctor Compaction ASTM D1557 - Modified Proctor
6-in mold
Material
Test Method
Coarse RCA
Method C
Fine RCA
Limestone
RCA+RAP
Class 6 Aggregate
Class 5Q Aggregate
S. Granular Borrow
LSSB NA
Sand Subgrade
Clay Loam
Method A
6-in mold
5 layers
56 blows per layer
Material passing 3/4-in sieve
(ASTM D1557)
4-in mold
4-in mold
5 layers
25 blows per layer
Material passing No. 4 sieve
NA = not available
(ASTM D1557)

80. LABORATORY TESTING Proctor Compaction
ASTM D4718 – Correction for oversize particles
Uncorrected – Test Data
Corrected
Material
MDD
OMC (%)
(pcf)
(kN/m3)
Coarse RCA
122.9
19.31
11.3
Fine RCA
121.6
19.10
11.1
Limestone
142.2
22.34
6.2
RCA+RAP
125.6
19.73 10
Class 6 Aggregate
128.2
20.14
8.3
Class 5Q Aggregate
122.6
19.26 11
S. Granular Borrow
138.6
21.77
5.4
LSSB NA
Sand Subgrade
136.6
21.46
5.7
Clay Loam
123.9
19.46
Material
Corrected MDD
Corrected OMC (%)
(pcf)
(kN/m3)
Coarse RCA
128.6
20.19
9.5
Fine RCA
121.7
19.12
11.1
Limestone
143.2
22.49
6.3
RCA+RAP
125.8
19.76
10.0
Class 6 Aggregate
8.3
Class 5Q Aggregate
128.0
20.11
9.6
S. Granular Borrow
140.3
22.03
5.3
LSSB NA
Sand Subgrade
137.7
21.63
5.6
Clay Loam
123.9
19.46
MDD = maximum dry density; OMC = optimum moisture content; NA = not available
MDD = maximum dry density; OMC = optimum moisture content; NA = not available

81. LABORATORY TESTING Stereophotography Camera Test material
Image station
Camera slider

82. LABORATORY TESTING
Sphericity:
Roundness:

83. LABORATORY TESTING Permeability Test Cell Number Sample ID
Material Description w
(%) γd
Ksat
pcf
kN/m3
(in/sec)
(cm/sec)
185
18517GS002
Coarse RCA
10.5
122.4
19.22
3.93E-05
9.97E-05
18517GS004
1.60E-04
4.06E-04
18517GS008
3.28E-04
8.34E-04
186
18617GS006
Fine RCA
10.9
121.1
19.02
2.09E-04
5.32E-04
18617GS007
1.94E-04
4.94E-04
18617GS008
1.33E-04
3.38E-04
188
18817GS005
Limestone
6.6
143.0
22.46
1.90E-05
4.82E-05
18817GS006
1.93E-05
4.89E-05
18817GS008
1.34E-05
3.41E-05
189
18917GS002
RCA+RAP
123.0
19.32
4.84E-05
1.23E-04
18917GS003
1.91E-04
4.85E-04
18917GS006
1.10E-04
2.80E-04
127
12717GS001
Class 6 Aggregate
4.2
112.4
17.65
3.31E-03
8.40E-03
12717GS002
3.9
2.90E-03
7.37E-03
12717GS003
4.4
114.2
17.95
2.78E-03
7.05E-03
12717GS004
110.5
17.36
5.28E-03
1.34E-02
228
22817GS001
Class 5Q Aggregate
113.0
17.75
9.41E-03
2.39E-02
22817GS002 7
106.1
16.67
2.07E-03
5.26E-03
22817GS003
5.3
111.1
17.46
4.61E-03
1.17E-02
22817GS004
6.3
108.6
17.06
2.10E-03
5.33E-03

84. LABORATORY TESTING Permeability Test Cell Number Sample ID
Material Description w
(%) γd
Ksat
pcf
kN/m3
(in/sec)
(cm/sec)
185
18517SS006
Sand Subgrade
4.5
119.2
18.73
8.50E-04
2.16E-03
18517SS007
3.7
119.9
18.83
6.57E-03
1.67E-02
186
18617SS006
4.78
115.5
18.14
1.69E-04
4.30E-04
18617SS007 4
2.54E-04
6.46E-04
188
18817SS006
Clay Loam
10.08
123.6
19.42
1.60E-07
4.07E-07
18817SS007
9.79
124.2
19.52
1.95E-07
4.95E-07
127
12717SS001
10.07
3.75E-08
9.53E-08
12717SS002
9.04
2.59E-07
6.58E-07
12717SS003
9.7
8.19E-08
2.08E-07
227
22717SS001
9.69
121.7
19.12
1.5E-07
3.92E-07

85. Degree of Compaction (%)
LABORATORY TESTING
Permeability Test
Material Description
Degree of Compaction (%) w
(%) γd
Ksat
pcf
kN/m3
(in/sec)
(cm/sec)
Coarse RCA
100
10.97
123.0
19.32
5.00E-05
1.27E-04 95
10.99
117.4
18.44
1.92E-04
4.88E-04 90
11.5
110.5
17.36
2.63E-04
6.68E-04
Fine RCA
11.07
121.7
19.12
1.88E-04
4.77E-04
11.06
115.5
18.14
3.90E-04
9.90E-04
11.05
109.2
17.16
3.98E-04
1.01E-03
Limestone
6.13
143.0
22.46
3.17E-05
8.05E-05
6.11
135.5
21.28
7.52E-05
1.91E-04
6.08
128.0
20.10
1.29E-04
3.28E-04
RCA+RAP
9.84
125.5
19.71
5.24E-05
1.33E-04
9.76
119.9
18.83
1.89E-04
4.79E-04
9.94
113.0
17.75
5.79E-04
1.47E-03
Clay Loam
10.78
5.39E-08
1.37E-07
10.92
116.7
18.34
5.94E-07
1.51E-06
10.53
111.1
17.46
2.70E-06
6.86E-06

86. Increasing Suction, Decreasing Saturation
LABORATORY TESTING
Soil-Water Characteristic Curve (SWCC) Test
Soil-Water Characteristic Curve (SWCC)
Increasing Suction, Decreasing Saturation
Hydraulic Conductivity Function (HCF)
(Lu and Likos 2004)

87. LABORATORY TESTING Soil-Water Characteristic Curve (SWCC) Test
Dry Sand
Saturation = 0.17
Saturation = 0.40
Saturation = 0.70
Saturation = 0.80

88. LABORATORY TESTING
Soil-Water Characteristic Curve (SWCC) Test

89. LABORATORY TESTING Soil-Water Characteristic Curve (SWCC) Test
Parameter
Cell Coarse RCA
Cell Fine RCA
18517GS002
18517GS004
18517GS008
18617GS006
18617GS007
18617GS008 θr θs
0.2765
0.2782
0.2866
0.3004
0.2812
0.2846 α
0.1508
0.2313
0.1174
0.1819
0.0317
0.0465 n
1.1597
1.1559
1.7310
1.1650
1.2091
1.1787 m
0.1377
0.1348
0.1475
0.1416
0.1730
0.1515
Parameter
Cell Limestone
Cell RCA+RAP
18817GS005
18817GS006
18817GS008
18917GS002
18917GS003
18917GS006 θr
0.0419
0.0221
0.0520
0.0070
0.0120 θs
0.2414
0.2467
0.2449
0.2997
0.2987
0.2540 α
0.1728
0.1909
0.1881
0.2805
0.2357
0.2960 n
1.6088
1.5436
1.6808
1.2397
1.2602
1.1700 m
0.3784
0.3522
0.4050
0.1934
0.2065
0.1453

90. SCHEDULE MONTHS TASKS Task 1 Task 2 Task 3 Task 4 Task 5 Task 6 Task 78 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
Task 1
Task 2
Task 3
Task 4
Task 5
Task 6
Task 7
Task 8
Task 9